Column
nyc_inspections_df <- nyc_inspections |>
mutate(boro = case_when(boro == 0 ~ NA,
TRUE ~ boro),
critical_flag = case_when(critical_flag == "Not Applicable" ~ NA,
TRUE ~ critical_flag),
inspection_date = case_when(inspection_date == "1900-01-01T00:00:00.000" ~ NA,
TRUE ~ inspection_date),
latitude = case_when(latitude == "0" ~ NA,
TRUE ~ as.numeric(latitude)),
longitude = case_when(longitude == "0" ~ NA,
TRUE ~ as.numeric(longitude)),
score = as.numeric(score))
Chart A: Average number of inspections per restaurant
## `summarise()` has grouped output by 'camis', 'longitude'. You can override
## using the `.groups` argument.